Titlebook: Knowledge Graphs and Big Data Processing; Valentina Janev,Damien Graux,Emanuel Sallinger Book‘‘‘‘‘‘‘‘ 2020 The Editor(s) (if applicable) a

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Chapter 1 Ecosystem of Big Dataervices has created opportunities for collecting/accumulating a large amount of data. While in the past corporations used to deal with static, centrally stored data collected from various sources, with the birth of the web and cloud services, cloud computing is rapidly overtaking the traditional in-

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Chapter 2 Knowledge Graphs: The Layered Perspective chapter, we are going to take the position that precisely in the multitude of definitions lies one of the strengths of the area. We will choose a particular perspective, which we will call the layered perspective, and three views on Knowledge Graphs.

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Chapter 4 Creation of Knowledge Graphsre details about the current prevalent ones. After reading this chapter, the reader should have an understanding of the different solutions available to generate Knowledge Graphs and should be able to choose the mapping language that best suits a certain use case.

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Chapter 8 Context-Based Entity Matching for Big Datam heterogeneous data sources. However, the RDF data model allows for describing entities under various contexts, e.g., people can be described from its demographic context, but as well from their professional contexts. Context-aware description poses challenges during entity matching of RDF datasets